A Switching Control Approach to Haptic Exploration for Quality Grasps

Robotic grasping is traditionally approached as a pure planning problem that assumesa priori knowledge of the target object’s geometry. However, we would like our robot to be able to robustly grasp objects with which it has no prior experience. Our approach is to use haptic information to drive a search process for appropriate finger contact locations . Given a cost function that is based on the total force and moment applied to the object by the set of contacts, and simple assumptions about the local surface geometry, this search process can be formulated as one of gradient descent on the cost function. Prior work in this area has assumed that the surface of the object local to the contact is either flat or convex . However, when the surface is concave, the search process, in fact, ascends the cost function. Here, we propose a switching controller approach that estimates the local curvature of the object over multiple contacts. This information is then used to switch between one of two methods of estimating the gradient of the cost function. While this new approach shows comparable performance to the original when faced with objects containing only flat or convex surfaces, the new algorithm performs substantially better when objects contain concave surfaces.